Abstract
In organizing household waste management and controlling waste collection and disposal, it is necessary to minimise risks to the environment and human health and, where possible, ensure that waste is recycled and returned to the economic cycle. Different models are being applied to increase waste collection management efficiency, but in recent years, the mobile phone data is widely used to solve various application problems. The research objective is to develop a waste collection model, which responds to the population’s current demands and allows planning waste container loading, based on mobile phone data statistics. The developed approach, techniques and data model can be used for waste container analysis and optimisation of their placement near small commercial structures, information kiosks, residential areas and other places attracting larger amounts of people. The developed relational data model includes information about mobile phone base stations, waste container data, calendar table and geographic location table. Further steps include data processing and data modelling in order to generate a data model for visual and quantitative analysis. The methods and data analysis techniques used in this research could be used to build a commercial product for mobile data operators allowing predicting the most appropriate placement of waste containers in any territory where mobile base station data is available. The choice of any of the proposed strategies allows achieving both direct benefits, like increasing the collected amount of recyclable glass, and indirect benefits – an increase in the amount of glass collected in the remaining containers.
| Original language | English |
|---|---|
| Title of host publication | Advances in Information and Communication - Proceedings of the 2020 Future of Information and Communication Conference FICC |
| Editors | Kohei Arai, Supriya Kapoor, Rahul Bhatia |
| Place of Publication | Cham |
| Publisher | Springer Nature Switzerland |
| Pages | 67-77 |
| Number of pages | 11 |
| Volume | 1130 AISC |
| ISBN (Print) | 9783030394417 |
| DOIs | |
| Publication status | Published - 2020 |
Publication series
| Name | Advances in Intelligent Systems and Computing |
|---|---|
| Volume | 1130 AISC |
| ISSN (Print) | 2194-5357 |
| ISSN (Electronic) | 2194-5365 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 11 Sustainable Cities and Communities
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SDG 12 Responsible Consumption and Production
OECD Field of Science
- 5.2 Economics and Business
- 1.2 Computer and Information Sciences
Keywords
- Conceptual architecture
- Functionality model
- Principal Component Analysis
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